For healthcare CEOs, boards, and investors

The people who can kill your AI do not work in AI.

I help CEOs and boards turn valuable but operationally complicated healthcare products into businesses that can scale. The model is almost never the problem. The problem is a decision that crosses regulatory, quality, security, privacy, clinical, and finance, and belongs to none of them.

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I have been on both sides of the table. I have been the vendor torn apart in a health system's security review, and I have been the one whose signature authorized use inside a $14B enterprise. More than 30 FDA-regulated products through those gates, as an operator.

Arvita Tripati

The gates I have been through

Delivered inside their regulated programs
Johnson & JohnsonGileadModernaAbbVieAmerican Red Cross

Their clinical trials, run from inside the technology vendor that delivered them.

Cleared their review, and bought
NHSU.S. Department of Veterans Affairs

An FDA-regulated wearable, through two of the most demanding enterprise buyers there are. Security, privacy, clinical, and procurement all had a veto. None of them used it.

Four functions hold a veto over AI in regulated healthcare: regulatory, quality, security, and privacy. I have held accountability in all four. More than 30 FDA-regulated products through those gates as an operator, not an advisor: AliveCor, LabCorp, Vineti, Korio, Clip Health, endpoint Clinical.

Find your situation

These look like five different problems. They are one problem.

A decision that crosses functions, and nobody who can make it. Every one of them arrives dressed as a technology question. None of them is.

Cost per encounter has not moved.The AI drafts every note. Someone still reviews every one. Adoption is real, clinicians like it, and the work never left the P&L. For healthcare services CEOs →
The pilot worked. The contract did not come.Six months in a health system's security, privacy, or clinical review, and the product team keeps insisting the product is fine. It is fine. That was never the problem. Book a call →
AI is in the value-creation plan. Nobody can show where the value is.Pilots launched, vendors signed, board decks ambitious, and no one can answer what the investment committee will ask. For operating partners →
We are underwriting AI claims nobody has pressure-tested.Commercial diligence tests the market. QoE tests the numbers. Neither tests whether the AI is a product, a feature, or a demo. For deal teams →
Nobody in this boardroom can evaluate our AI risk disclosure.The committee keeps bouncing pilots back and cannot articulate why. Someone is going to sign this, and they know it. Book a call →

In every one of them, someone's name goes on the decision. That is why it does not get made.

An operator, not an AI strategist

AI value creation in healthcare sits where product, workflow, regulation, evidence, data, commercial strategy, privacy, quality, implementation, and organizational design meet. The problems blocking value rarely belong to one function, and adding another tool almost never fixes them.

I have spent nearly two decades inside those functions, bringing more than 30 regulated healthcare products to market.

I have never been a banker, and that is the point. The people who can read a model are not usually the people who have shipped a regulated AI product, sat through the FDA inspection, and watched an enterprise deal stall in a security review. I have. When I tell you an assumption will not survive contact with a health system, it is because I have been on the other side of that conversation.

I am not an implementation shop looking for a transformation program. I am not here to validate an AI story leadership has already decided to tell.

My job is to tell you where the value is real, where the assumptions are weak, what to fund, fix, defer, or stop, and what operating model gets the result. And where you want it, to make the call myself.

Four gates that stopped being bottlenecks

Each of these is a mechanism, not a number on its own. That is what makes them survive the follow-up question. None of them was solved by a better model.

6 weeks→a day and a half
Client delivery documentation at a healthtech SaaS company, drafted by AI agents. Then the review threshold came down, twice. Project managers stopped writing documents and started carrying more engagements.
4 months→3 weeks
Cut delivery cycle time for a GxP-regulated SaaS platform, through risk-based testing and automation aligned to the release cadence. The client launched early, and put the value of that early launch at $81M.
reactive tickets→7% off support spend
Complaints analysis at an FDA-regulated wearables company that fixed root causes instead of processing tickets. Complaints are a regulatory function. It paid like an operating one.
5 people→17, zero turnover
Built compliance and information security from scratch at a healthtech SaaS company. Audit requests fell 35%. The function returned 57% on its cost.

Ways to work with me

Fixed scope, fixed date, both agreed in writing before any work begins. No hourly billing, no staffing pyramid, no change orders.

AI Plan Teardown

Free · back in 5 business days

Write me a paragraph on each of your three biggest AI bets: what each is meant to do, what it has cost, and roughly what share of its output still gets human review. That last number is usually the whole answer. You get the three weakest assumptions back, in writing. Read it, then decide whether we should talk. No deck, no NDA, no data.

Request the teardown

Pre-IC Diligence Sprint

5 business days

A written read on the AI in a target: what is product, what is feature, what is roadmap, what is demo. The claims exposure. The integration economics, including the preconditions nobody priced. Written for the IC memo.

Read the diligence page

AI Operating Blueprint

30 days

Ranked initiatives, implementation economics, review burden, adoption constraints, decision rights, named owners, board measures, and a 90-day execution plan. For a company where AI is in the plan and the value has not shown up.

Read the CEO page

Fractional Chief AI Officer

6 to 12 months · I make the decisions, not just recommend them

The title is the shorthand. The substance is decision rights. You give me authority over a defined set of cross-functional AI calls, and I make them. Which calls are mine is the scope, agreed and signed before I start. This is what created the six weeks. It is the only thing that ever does.

What I actually own

Most AI advice ends in a document. Somebody still has to make the call.

And in regulated healthcare, the person who makes it is the person whose name is on the incident report. That is why it does not get made.

At a healthtech SaaS company, every client engagement opened with the same three documents: a project plan, a requirements specification, and a risk assessment. Six weeks to produce them. The engagement did not move until they were done.

Everything those documents needed already existed, in the proposal and the intake form. The six weeks were not spent finding information. They were spent transcribing it, formatting it, and routing it. We built agents to draft all three. The draft came back in a day and a half.

That is where almost every AI rollout stops. A fast draft that still gets read end to end by the same person who used to write it has not removed any work. It has moved it.

So I set the review threshold. What a human still had to read, what they could sign without reading, and what nobody needed to look at again. I made that call, which meant I owned it if it went wrong.

It did not go wrong. At six months we cut review further and put monitoring behind it. At twelve months we cut it again. The reduction was scheduled, not requested.

Project managers stopped producing documents and started running more engagements. The same team carried more projects.

The threshold is the decision your organization is avoiding. It is uncomfortable because it has a name attached to it, and if it goes wrong that name is on the incident report. That discomfort is what sits between you and the margin. As Fractional Chief AI Officer, the name is mine.

They hired me to find what nobody else would.

“Arvita crushes challenging problems and creates order where there is uncertainty. I hired her, and she became an integral member of the leadership team. I hired her again to join me on the founding team at Korio.”

Chuck Harris
Former CEO, endpoint Clinical (acquired by LabCorp)
COO & Co-founder, Korio

“I love Arvita's discipline and the structure of her thinking. Her work was thorough, well-organized, and genuinely useful.”

Drew Bennett
Innovation Partnerships
University of Michigan

Prefer a peer room to a 1:1 engagement?

The CEO Circles put you in a confidential, curated room with five other healthcare or healthtech CEOs working through the same decisions. One of the eight sessions belongs to you, and the whole room works your decision.

Explore the CEO Circles

Nobody is stuck on the model.

They are stuck on a decision that crosses four functions, carries personal risk, and has no owner. If that is where you are, the next step is not another pilot. It is a better operating decision, and someone willing to sign it.

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